Enhanced Mono/Divalent Ion Separation via Charged Interlayer Channels in Montmorillonite-Based Membranes.

Efficient mono- and divalent ion separation is pivotal for environmental conservation and energy utilization. Two-dimensional (2D) materials featuring interlayer nanochannels exhibit unique water and ion transport properties, rendering them highly suitable for water treatment membranes. In this work, we incorporated polydopamine/polyethylenimine (PDA/PEI) copolymers into 2D montmorillonite (MMT) nanosheet interlayer channels through electrostatic interactions and bioinspired bonding. A modified laminar structure was formed on the substrate surface via a straightforward vacuum filtration. The electrodialysis experiments reveal that these membranes could achieve monovalent permselectivity of 11.06 and Na+ flux of 2.09 × 10-8 mol cm-2 s-1. The enhanced permselectivity results from the synergistic effect of electrostatic and steric hindrance effect. In addition, the interaction between the PDA/PEI copolymer and the MMT nanosheet ensures the long-term operational stability of the membranes. Theoretical simulations reveal that Na+ has a lower migration energy barrier and higher migration rate for the modified MMT-based membrane compared to Mg2+. This work presents a novel approach for the development of monovalent permselective membranes.

Bistatic Doppler wind lidar study for wind field measurement over complex terrain.

Atmospheric wind measurement over complex terrain is of great significance. Due to the limitation of the retrieval method, a single wind lidar cannot be applied to detect the horizontally inhomogeneous wind field. Therefore, a bistatic Doppler wind lidar system is studied for meeting the requirement of wind detection over complex terrain. By analyzing the uncertainty of a synthetic wind field, the isosceles triangle is proven to be the optimal layout of the bistatic lidar system. By using the data set of Nanjing sounding data from 2015 and two typical wind field models, the detection accuracy of the bistatic lidar system is estimated. The experimental results show that the bistatic wind lidar can detect the wind field over complex terrain accurately, the wind errors are less than 1 m/s below 4 km, and the relative errors are less than 5%.

Impact of solar background radiation on the accuracy of wind observations of spaceborne Doppler wind lidars based on their orbits and optical parameters.

Due to the quantum properties of light, solar background radiation (SBR) is the main source of noise in daytime wind observations of spaceborne Doppler wind lidars (DWLs). In previous works, the impact of SBR on the observation accuracy of spaceborne lidars was assessed mainly using the default or worst-case scenarios. We assessed the impact of SBR on the observations of spaceborne DWLs using the global distributions of SBR in summer and winter, which were obtained based on their orbit parameters, view geometry and optical parameters. Three experiments illustrate that the uncertainty in wind observations increases with an increase in the quantiles of SBR. The uncertainties of the whole profiles of wind are greater than 2 m s-1 in the troposphere and 3 m s-1 in the stratosphere when the quantile of the SBR is greater than 85% in summer and 95% in winter, which do not satisfy the accuracy expectations of the European Space Agency (ESA) for spaceborne DWLs. The facts indicate that the impact of SBR cannot be negligible for the observations of spaceborne DWLs. Based on the orbit parameters, view geometry, and optical parameters of new spaceborne DWLs, engineers can assess the impact of SBR on the accuracy of wind observations from a global perspective using the method proposed in this paper.

Simulation and assessment of solar background noise for spaceborne lidar.

The properties for six typical land cover types and three sky conditions were derived in this paper, which allows to make seasonal upper estimations of solar background radiation for a given atmospheric scenario. Solar background noise can be derived from the estimations for a spaceborne lidar based on optical parameters. Comparisons among simulated solar background noise and measurements of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and a Moderate Resolution Imaging Spectroradiometer (MODIS) demonstrate the feasibility of this method. The upper estimates of solar background radiation can be used for lidar engineers to assess the upper estimates of solar background noise for given atmospheric scenarios, which would be a step forward in comparison with using the worst-case scenario everywhere.

[Research on Cloud Phase Detemination Using Infrared Emissivity Spectrum Data (2): Retrieval of Cloud Effective Radius and Water Path].

The cloud microphysical properties such as cloud effective radius and cloud water path are fundamental properties for understanding the cloud formation, radiative impacts and interactions with aerosol and precipitation. The downwelling infrared radiance spectra is studied here to retrieve microphysical properties of clouds. The sensitivity of the downwelling radiance spectra and cloud emissivity spectra to the liquid cloud and ice cloud effective radius and optical depth is analyzed. The look-up-tables are established for optically thin clouds (cloud optical depth less than 6) that rely on parameters of the slopes and differences of the emissivity spectra. These parameters include the difference in the emissivity between 862.1 and 934.9 cm(-1), the difference in the emissivity between 1 900.1 and 2 170.1 cm(-1), the slope of the cloud emissivity and the radiation between 900 and 1 000 cm(-1), the slope of the cloud emissivity and the radiation between 1 100 and 1 200 cm(-1). The look-up-tables are constrained by the incorporation of mean ozone band transmissivity between 1 050 and 1 060 cm(-1). Cloud effective radius and optical depth can be obtained with by least squares fitting between observed and modeled above-mentioned multiple spectral parameters. The cloud water path can then be derived from the experiential relationship. The inversion results are compared with the ARM baseline cloud microphysics product (MICROBASE). It is shown that, the cloud effective radius is roughly in the same order of magnitude while the water paths derived from both method are of large differences especially for the liquid cloud path. The algorithm proposed in this paper is efficient for retrieving microphysical properties of thin clouds with cloud optical depth less than 6.

[Research on Cloud Phase Detemination Using Infrared Emissivity Spectrum Data (1): Cloud Phase Determination].

As a key factor in the climate model, cloud phase is an important prerequisite to performing cloud property retrievals from remote sensor measurements. The ability to infer cloud phase using cloud emissivity spectra is investigated by numerical simulations. It is shown that for emissivity below 0.95, several spectral features such as the slopes, the ratios and the differences of the emissivity are consistent with the variation of cloud phase in some spectral regions. Specifically, these features include the slope of the cloud emissivity between 800 and 900 cm(-1), the slope of the cloud emissivity between 900 and 1 000 cm(-1), the difference in the mean emissivity between above-mentioned two regions, the ratio of the emissivity at 862.1 cm(-1) to the emissivity at 989.8 cm(-1), the difference in the emissivity between 862.1 and 989.8 cm(-1), the ratio of the emissivity at 1 900.1 cm-1 to the emissivity at 2 029.3 cm-1, the ratio of the mean emissivity for far-infrared region to the emissivity at 900 cm(-1). A cloud phase classifier is proposed based on support vector machines (SVM). A series of simulations including various cloud patterns are performed. The RBF kernel function parameters and the penalty factor of SVM are selected by using the genetic algorithm. The phase determination algorithm is applied for collecting data from the AERI at the SGP site. The results from the ground-based multisensor cloud phase classifier proposed by Shupe are used to validate the phase determination algorithm. It is found the two results are consistent in general. 30% clouds are indicated as opaque due to its high emissivity. The cloud with small lidar's depolarization is misclassified as clear sky by the Shupe method. It can be concluded that the proposed algorithm considering the spectral information (spectral slopes, ratios and differences) is efficient for cloud phase determination of thin cloud.

The impact of CACNA1C allelic variation on regional gray matter volume in Chinese population.

The SNP rs1006737 in CACNA1C gene has been significantly associated with psychiatric disorders (e.g., schizophrenia and bipolar disorder) in European populations. In Han Chinese, rs1006737 is also strongly associated with schizophrenia, although the effects of the psychosis risk SNP on related brain functions and structures in this population remain unclear. Here, we examined the association of rs1006737 with gray matter volume in a sample of 278 healthy Han Chinese. A whole-brain voxel-based morphometry (VBM) analysis revealed a significant association in the region around right superior occipital gyrus (family-wise error corrected, P = 0.023). Our data provides initial evidence for the involvement of this psychosis genetic risk locus in brain structure variations in Chinese population, and calls for further investigations.

Effects of hypertension on subcortical nucleus morphological alternations in patients with type 2 diabetes.

Objectives: Type 2 diabetes mellitus(T2DM) and hypertension(HTN) are common comorbidities, and known to affect the brain. However, little is known about the effects of the coexisting HTN on brain in T2DM patients. So we aim to investigate the impact of HTN on the subcortical nucleus morphological alternations in T2DM patients. Materials & methods: This work was registered by the clinicaltrials.gov (grant number NCT03564431). We recruited a total of 92 participants, comprising 36 only T2DM patients, 28 T2DM patients with HTN(T2DMH) and 28 healthy controls(HCs) in our study. All clinical indicators were assessed and brain image data was collected for each participant. Voxel-based morphometry(VBM), automatic volume and vertex-based shape analyses were used to determine the subcortical nucleus alternations from each participant's 3D-T1 brain images and evaluate the relationship between the alternations and clinical indicators. Results: T2DMH patients exhibited volumetric reduction and morphological alterations in thalamus compared to T2DM patients, whereas T2DM patients did not demonstrate any significant subcortical alterations compared to HCs. Furthermore, negative correlations have been found between thalamic alternations and the duration of HTN in T2DMH patients. Conclusion: Our results revealed that HTN may exacerbate subcortical nucleus alternations in T2DM patients, which highlighted the importance of HTN management in T2DM patients to prevent further damage to the brain health.

Contrast enhanced magnetic resonance imaging-based radiomics nomogram for preoperatively predicting expression status of Ki-67 in meningioma: a two-center study.

Background: The aim of this study was to develop and validate a radiomics nomogram for preoperative prediction of Ki-67 proliferative index (Ki-67 PI) expression in patients with meningioma. Methods: A total of 280 patients from 2 independent hospital centers were enrolled. Patients from center I were randomly divided into a training cohort of 168 patients and a test cohort of 72 patients, and 40 patients from center II served as an external validation cohort. Interoperator reproducibility test, Z-score standardization, analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO) binary logistic regression were used to select radiomics features, which were extracted from contrast-enhanced T1-weighted imaging (CE-T1WI) imaging. The radiomics signature for predicting Ki-67 PI expression was developed and validated using 4 classifiers including logistic regression (LR), decision tree (DT), support vector machine (SVM), and adaptive boost (AdaBoost). Finally, combined radiological characteristics with radiomics signature were used to establish the nomogram to predict the risk of high Ki-67 PI expression in patients with meningioma. Results: Fourteen radiomics features were used to construct the radiomics signature. The radiomics nomogram that incorporated the radiomics signature and radiological characteristics showed excellent discrimination in the training, test, and validation cohorts with areas under the curve of 0.817 (95% CI: 0.753-0.881), 0.822 (95% CI: 0.727-0.916), and 0.845 (95% CI: 0.708-0.982), respectively. In addition, the calibration curve for the nomogram demonstrated good agreement between prediction and actual observation. Conclusions: The proposed contrast enhanced magnetic resonance imaging (MRI)-based radiomics nomogram could be an effective tool to predict the risk of Ki-67 high expression in patients with meningioma.

Transgenic rhesus monkeys carrying the human MCPH1 gene copies show human-like neoteny of brain development.

Brain size and cognitive skills are the most dramatically changed traits in humans during evolution and yet the genetic mechanisms underlying these human-specific changes remain elusive. Here, we successfully generated 11 transgenic rhesus monkeys (8 first-generation and 3 second-generation) carrying human copies of MCPH1, an important gene for brain development and brain evolution. Brain-image and tissue-section analyses indicated an altered pattern of neural-cell differentiation, resulting in a delayed neuronal maturation and neural-fiber myelination of the transgenic monkeys, similar to the known evolutionary change of developmental delay (neoteny) in humans. Further brain-transcriptome and tissue-section analyses of major developmental stages showed a marked human-like expression delay of neuron differentiation and synaptic-signaling genes, providing a molecular explanation for the observed brain-developmental delay of the transgenic monkeys. More importantly, the transgenic monkeys exhibited better short-term memory and shorter reaction time compared with the wild-type controls in the delayed-matching-to-sample task. The presented data represent the first attempt to experimentally interrogate the genetic basis of human brain origin using a transgenic monkey model and it values the use of non-human primates in understanding unique human traits.

Identify changes of brain regional homogeneity in early and later adult onset patients with first-episode depression using resting-state fMRI.

OBJECTIVE: Previous work exhibited different brain grey matter volume (GMV) changes between patients with early adult onset depression (EOD, age 18-29) and later adult onset depression (LOD, age 30-44) by using 30-year-old as the cut-off age. To identify whether regional homogeneity (ReHo) changes are also different between EOD and LOD by using same cut-off age, we used resting-state functional magnetic resonance imaging (fMRI) to detect the abnormal ReHo between patients with EOD and LOD in the present study. METHODS: Resting-state fMRI scans of 58 patients with EOD, 62 patients with LOD, 60 young healthy controls (HC), and 52 old HC were obtained. The ReHo approach was used to analyze the images. RESULTS: The ANOVA analysis revealed that the ReHo values in the frontoparietal, occipital, and cerebellar regions were significantly different among the four groups. Relative to patients with LOD, patients with EOD displayed significantly increased ReHo in the left precuneus, and decreased ReHo in the right fusiform. The ReHo values in the left precuneus and the right fusiform had no significant correlation with the score of the depression rating scale or illness duration in both patient subgroups. Compared to young HC, patients with EOD showed significantly increased ReHo in the right frontoparietal regions and the right calcarine. Furthermore, the increased ReHo in the right frontoparietal regions, right insula and left hippocampus, and decreased ReHo in the left inferior occipital gyrus, right middle occipital gyrus, left calcarine, and left supplementary motor area were observed in patients with LOD when compared to old HC. CONCLUSIONS: The ReHo of brain areas that were related to mood regulation was changed in the first-episode, drug-naive adult patients with MDD. Adult patients with EOD and LOD exhibited different ReHo abnormalities relative to each age-matched comparison group, suggesting that depressed adult patients with different age-onset might have different pathological mechanism.

Childhood maltreatment is associated with gray matter volume abnormalities in patients with first-episode depression.

Previous neuroimaging studies suggest that childhood maltreatment (CM) can affect brain function and structure and constitutes a potent risk of developing depression. The present study attempts to differentiate the effect of CM from the impact of depression diagnosis on brain structure. Eighty-four patients with first-episode depression and 84 controls participated in this study. All subjects underwent a structural magnetic resonance imaging (MRI) scan. Voxel-based morphometric analysis of variance (ANOVA), between-group comparison, and regression analyses were performed on a whole-brain level to identify the unbiased effects of CM and depression on brain structure. Our data showed different main effects of CM and depression on brain structure separately: the significant main effect of CM on fronto-limbic areas, visual cortex and cerebellum, and the main effect of depression on orbitofrontal regions and bilateral temporal lobes. The maltreatment-by-diagnosis interaction effect was found located on the bilateral prefrontal cortex. The CM severity was negatively related with the inferior occipital volume and positively with volumes in the left dorsolateral prefrontal cortex, right caudate, and left middle temporal gyrus. This study suggested that early life stress like CM is associated with structural abnormalities of the fronto-limbic regions that are commonly regarded as the psychopathological consequence of depression. The effect of CM on brain structure should be considered in future neuroimaging research of depression.

Alternations of White Matter Structural Networks in First Episode Untreated Major Depressive Disorder with Short Duration.

It is crucial to explore the pathogenesis of major depressive disorder (MDD) at the early stage for the better diagnostic and treatment strategies. It was suggested that MDD might be involving in functional or structural alternations at the brain network level. However, at the onset of MDD, whether the whole brain white matter (WM) alterations at network level are already evident still remains unclear. In the present study, diffusion MRI scanning was adopt to depict the unique WM structural network topology across the entire brain at the early stage of MDD. Twenty-one first episode, short duration (<1 year) and drug-naïve depression patients, and 25 healthy control (HC) subjects were recruited. To construct the WM structural network, atlas-based brain regions were used for nodes, and the value of multiplying fiber number by the mean fractional anisotropy along the fiber bundles connected a pair of brain regions were used for edges. The structural network was analyzed by graph theoretic and network-based statistic methods. Pearson partial correlation analysis was also performed to evaluate their correlation with the clinical variables. Compared with HCs, the MDD patients had a significant decrease in the small-worldness (σ). Meanwhile, the MDD patients presented a significantly decreased subnetwork, which mainly involved in the frontal-subcortical and limbic regions. Our results suggested that the abnormal structural network of the orbitofrontal cortex and thalamus, involving the imbalance with the limbic system, might be a key pathology in early stage drug-naive depression. And the structural network analysis might be potential in early detection and diagnosis of MDD.

Abnormal functional connectivity of the amygdala in first-episode and untreated adult major depressive disorder patients with different ages of onset.

Major depressive disorder (MDD) is a common mental disorder with high morbidity. As a part of the limbic system, the amygdala is important in the processing of emotional information. Structural and functional connectivity (FC) abnormalities in the amygdala have been observed in MDD patients. The present study was carried out to identify the features of amygdala FC in adult MDD patients with different ages of onset. Sixty-nine first-episode and untreated MDD patients and 81 healthy controls (CTLs) were included in this study and underwent 3D structural imaging and resting-state functional MRI scanning. The patients and CTLs were divided into two groups according to age of onset: young adult (<30 years old) and old adult (≥30 years old). Voxel-based morphometry methods were used to investigate volume differences in MDD patients with different ages of onset at the whole-brain level. Then, the resting-state FC of bilateral amygdala seeds to the whole brain of MDD patients and matched CTLs in these two different onset age groups were analysed. We found that the volume of the bilateral amygdala increased to a greater extent in young adult patients compared with old adult patients. We also observed a trend toward different amygdala FC by onset age in MDD patients. In young adult patients, the left amygdala showed more abnormal resting-state FC with other regions compared with matched controls. However, in old adult patients, compared with matched controls, the right amygdala showed more abnormal changes in the resting-state FC with other regions. MDD patients with different ages of onset showed different changes in the structure and FC of the amygdala. These results might help us to understand the high heterogeneity of MDD.

Study on the pathogenic mechanism of Broca's and Wernicke's aphasia.

OBJECTIVE: To study the mechanisms of aphasia by observing cerebral blood flow and metabolism changes in language functional areas of the brain using imaging, in order to develop a language rehabilitation plan for aphasia patients. METHODS: Fifty-eight patients who suffered from Broca's or Wernicke's aphasia secondly to cerebral infarction were evaluated using the Western aphasia battery and Frenchay dysarthria assessment. CT and MRI were obtained to identify the location of lesions, and the language areas were analysed with magnetic resonance spectroscopy (MRS) and perfusion-weighted imaging (PWI). The results were compared with those of the contralateral hemisphere. RESULTS: Of the 58 patients, there were 23 Broca's aphasia patients, 29 Wernicke's aphasia patients and six other aphasia types. We excluded five patients accompanied by dysarthria, six patients with other aphasia types and 14 patients with much more disease lesions. Finally, we analysed the remaining 12 Broca's aphasia and 21 Wernicke's aphasia patients by MRS and PWI. MRS shows that the N-acetylaspartate, choline and creatine of the Broca's or Wernicke's area were reduced than those of the contralateral hemisphere, while PWI results show that the damaged Broca's or Wernicke's areas were in a hypoperfusion state. CONCLUSIONS: Broca's or Wernicke's area of aphasia patients exhibits hypoperfusion and hypometabolism, indicating that they might be the mechanisms of Broca's or Wernicke's aphasia.

Changes of grey matter volume in first-episode drug-naive adult major depressive disorder patients with different age-onset.

OBJECTIVE: Little is known about the pathological mechanism of early adult onset depression (EOD) and later adult onset depression (LOD). We seek to determine whether grey matter volume (GMV) change in EOD and LOD are different, which could also delineate EOD and LOD. METHODS: In present study, 147 first-episode, drug-naive patients with major depressive disorder (MDD), age between 18 and 45, were divided into two groups on the basis of age of MDD onset: the early adult onset group (age 18-29) and the later adult onset group (age 30-44), and a total of 130 gender-, and age-, matched healthy controls (HC) were also divided into two groups which fit for each patient group. Magnetic resonance imaging was conducted on all subjects. The voxel-based morphometry (VBM) approach was employed to analyze the images. RESULTS: Widespread abnormalities of GMV throughout parietal, temporal, limbic regions, occipital cortex and cerebellum were observed in MDD patients. Compare to young HC, reduced GMV in right fusiform gyrus, right middle temporal gyrus, vermis III and increased GMV in right middle occipital gyrus were seen in the EOD group. In contrast, relative to old HC, decreased GMV in the right hippocampus and increased GMV in the left middle temporal gyrus were observed in the LOD group. Compared to the LOD group, the EOD group had smaller GMV in right posterior cingulate cortex. There was no significant correlation between GMV of the right posterior cingulate cortex and the score of the depression rating scale in patients group. CONCLUSIONS: The GMV of the brain areas that were related to mood regulation was decreased in the first-episode, drug-naive adult patients with MDD. Adult patients with EOD and LOD exhibited different GMV changes relative to each age-matched comparison group, suggesting depressed adult patients with different age-onset might have different pathological mechanism.

The volumetric and shape changes of the putamen and thalamus in first episode, untreated major depressive disorder.

Previous MRI studies confirmed abnormalities in the limbic-cortical-striatal-pallidal-thalamic (LCSPT) network or limbic-cortico-striatal-thalamic-cortical (LCSTC) circuits in patients with major depressive disorder (MDD), but few studies have investigated the subcortical structural abnormalities. Therefore, we sought to determine whether focal subcortical grey matter (GM) changes might be present in MDD at an early stage. We recruited 30 first episode, untreated patients with major depressive disorder (MDD) and 26 healthy control subjects. Voxel-based morphometry was used to evaluate cortical grey matter changes, and automated volumetric and shape analyses were used to assess volume and shape changes of the subcortical GM structures, respectively. In addition, probabilistic tractography methods were used to demonstrate the relationship between the subcortical and the cortical GM. Compared to healthy controls, MDD patients had significant volume reductions in the bilateral putamen and left thalamus (FWE-corrected, p < 0.05). Meanwhile, the vertex-based shape analysis showed regionally contracted areas on the dorsolateral and ventromedial aspects of the bilateral putamen, and on the dorsal and ventral aspects of left thalamus in MDD patients (FWE-corrected, p < 0.05). Additionally, a negative correlation was found between local atrophy in the dorsal aspects of the left thalamus and clinical variables representing severity. Furthermore, probabilistic tractography demonstrated that the area of shape deformation of the bilateral putamen and left thalamus have connections with the frontal and temporal lobes, which were found to be related to major depression. Our results suggested that structural abnormalities in the putamen and thalamus might be present in the early stages of MDD, which support the role of subcortical structure in the pathophysiology of MDD. Meanwhile, the present study showed that these subcortical structural abnormalities might be the potential trait markers of MDD.

[A DTI study of the contralateral corticospinal tract modeled through simulated intracranial space-occupying lesions in macaque brain motor areas].

Recent studies found that a loss of motor function following corticospinal tract (CST) damage can, to some extent, be restored. Few studies, however, examine how space-occupying lesions in the brain motor area may affect the contralateral CTS structure and function. We performed a simulation of intracranial space-occupying lesions in the brain motor area by implanting of balloons into the brains of the two healthy macaques. Diffusion tensor imaging (DTI) was performed on the macaques' brains four times to measure the FA values of the contralateral CST operative area. The results showed that on the day of balloon implantation, the FA values had no obvious effect, but with time the effect increased, becoming increasingly apparent one week after removing the balloons. Experimental results demonstrated that this model was both feasible and reliable. After the simulated space-occupying lesions occurred in the brain motor area, DTI showed a compensatory response of the contralateral CTS, which remained for a short period of time even after the lesions were removed. This result suggests that the contralateral CST may then also contribute to recovery of limb function.

Altered lipid droplet dynamics in hepatocytes lacking triacylglycerol hydrolase expression.

Lipid droplets (LDs) form from the endoplasmic reticulum (ER) and grow in size by obtaining triacylglycerols (TG). Triacylglycerol hydrolase (TGH), a lipase residing in the ER, is involved in the mobilization of TG stored in LDs for the secretion of very-low-density lipoproteins. In this study, we investigated TGH-mediated changes in cytosolic LD dynamics. We have found that TGH deficiency resulted in decreased size and increased number of LDs in hepatocytes. Using fluorescent fatty acid analogues to trace LD formation, we observed that TGH deficiency did not affect the formation of nascent LDs on the ER. However, the rate of lipid transfer into preformed LDs was significantly slower in the absence of TGH. Absence of TGH expression resulted in increased levels of membrane diacylglycerol and augmented phospholipid synthesis, which may be responsible for the delayed lipid transfer. Therefore, altered maturation (growth) rather than nascent formation (de novo synthesis) may be responsible for the observed morphological changes of LDs in TGH-deficient hepatocytes.